In the operating room, the anesthesiologist needs to assess the patient's condition and adjust the therapy using a wide variety of distinct medical devices. These devices often don't talk to each other, and hence only provide one piece of the picture. Clinicians have to mentally keep track of the patient's level of sedation, analgesia and relaxation based on the amount of drugs they've administered, and their familiarity with the drug's pharmacokinetic and pharmacodynamic (PK/PD) models.
The practice of intra-operative anesthesia typically involves administering sedative, analgesic and neuromuscular relaxants to a patient. These drugs manage the patient's level of consciousness, pain management and neuromuscular blockade. Typically, each drug has a PK/PD model that specifies what the body does to the drug (pk) and how the drug interacts with the body (pd). These models are usually derived in isolation. In a clinical setting, multiple drugs are typically used together.
Three-dimensional response surfaces have been developed to represent the interaction between two drugs. These surfaces represent the probability of non-response to a specific effect at different concentrations of the two drugs. This can also be considered an interactive (or synergistic) pd model. The challenge is to display these varying probabilities on a 2d graph that can be easily interpreted by a clinician during anesthesia.
The issue is confounded even more when there is more than one effect to display on the same graph. For example, when considering analgesia, one can consider varying levels of pain such as high pain (intubation) and low pain (post-operative anesthesia). The challenge is to display these related but distinct surfaces on the same two-dimensional graph. The display should consist of the (effect site) concentration of the analgesic drug(s) (which is at least one input to the 3d surface), the probability of each displayed effect, and reference points to those effects (such as 50% to 95% probability).
Prior work by Medvis & the University of Utah developed a display to show PK/PD models to the clinician in real time. This work did not factor in some of the safety issues needed to safely use the system in a clinical environment. For example, it showed the models for inhaled agents as soon as the patient monitor detected them. The problem with this approach is that small traces of agents may be left over in the breathing circuit, although they are not largely part of the anesthesia plan for the patient.
Another issue not addressed in the prior art is how to handle communication errors with the connected devices. The display is fully reliant on getting accurate and timely information from the connected devices, specifically the anesthesia machine, patient monitor and/or IV pumps. If communication is severed, there is no clear path for what the display should show.
Another concern with known systems is that clinicians can continue old cases, instead of starting new ones. This is problematic since the previous patient's drug levels might be included with the next patient's levels, and that would lead to inaccurate predictions.